What This Category's Data Looks Like
Data for this category comes from national public resource trading platforms, local trading platforms, engineering approval systems, and bidding and tendering supervision systems. The update frequency is daily. Daily business documents include bidding announcements, pre-qualification documents, bidding documents, tender documents, bid evaluation reports, successful bid candidate announcements, and successful bid result announcements. Data covers the entire bidding and tendering process for engineering construction projects, and includes core fields such as section division, qualification requirements, bid evaluation records, and objection and complaint handling. No extra custom units are used, and all fields follow relevant business specifications for bidding and tendering.
Constraints Imposed on Forms and Interactions by These Characteristics
The daily updated large volume of bidding documents requires form interactions to support batch document parsing and segmented processing, to avoid overload from single-round input. The fixed structure of multiple types of business documents requires forms to preset parsing templates for corresponding documents, adapting to field extraction logic for different files such as bidding announcements and bid evaluation reports. Compliance requirements associated with bidding and tendering data require the interaction link to add keyword verification related to party building learning, to block non-compliant content. Processing needs for large documents (such as 100,000-character Chinese Word files, 15,000-row Excel files) require forms to support chunked upload and multi-turn dialogue connection, to avoid single-request timeouts.
Configuration Settings
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
formInput | 800–1200 characters | Adapts to the input length of single-round party building Q&A, avoids exceeding the basic context limit of FastGPT v4.17.0 |
| Single input limit | 1000 MB | Adapts to upload needs for large bidding documents (such as 100,000-character Chinese Word files, 15,000-row Excel files), supports batch import of full-process bidding and tendering data |
| Keyword interception trigger | Calibrated based on actual testing | Must block non-compliant bidding and tendering keywords and content unrelated to party building learning, to ensure Q&A compliance |
userSelect | Top 5 recall results | A large number of bidding documents, limiting the number of recalled results avoids information overload during interaction and improves Q&A efficiency |
| Context window length | 4000–6000 token | Adapts to context association needs for multi-turn party building learning Q&A, connects bidding document parsing and Q&A content |
Three Common Misconfigurations
- Phenomenon: Output content includes the phrase "Quote Marker: [1]". Cause: No filtering rules for quote markers in Q&A output are configured, and original annotated information retrieved from the knowledge base is returned directly.
- Phenomenon: Custom interface replies are not triggered after a user enters a specified keyword. Cause: Keyword trigger logic is not configured in the form interaction link, or trigger conditions are set incorrectly.
- Phenomenon: Incomplete command prompts are returned after large bidding documents are uploaded. Cause: Chunked upload or multi-turn dialogue connection is not configured, and a single request exceeds the system processing limit.
How to Confirm Configuration Is Complete
- Upload a test bidding announcement document, initiate a party building-related Q&A, check that the output does not include the phrase "Quote Marker: [1]".
- Enter preset non-compliant keywords, confirm that the system triggers interception and prompts for compliance requirements.
- Upload a 15,000-row Excel file of bidding and tendering data, confirm that the system can parse normally and supports multi-turn dialogue connection.
- Test an input length of 1300 characters for
formInput, confirm that no input over-limit error occurs.
The values provided are common starting points and should be measured against the reader's own samples.
Question material comes from public community discussions. Configuration values are common starting points and should be measured against your own samples. Verified on 2026-09-28.